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How algorithms create and prevent fa...
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Giansiracusa, Noah.
How algorithms create and prevent fake newsexploring the impacts of social media, deepfakes, GPT-3, and more /
紀錄類型:
書目-電子資源 : Monograph/item
正題名/作者:
How algorithms create and prevent fake newsby Noah Giansiracusa.
其他題名:
exploring the impacts of social media, deepfakes, GPT-3, and more /
作者:
Giansiracusa, Noah.
出版者:
Berkeley, CA :Apress :2021.
面頁冊數:
xii, 235 p. :ill., digital ;24 cm.
Contained By:
Springer Nature eBook
標題:
Fake newsPrevention.
電子資源:
https://doi.org/10.1007/978-1-4842-7155-1
ISBN:
9781484271551$q(electronic bk.)
How algorithms create and prevent fake newsexploring the impacts of social media, deepfakes, GPT-3, and more /
Giansiracusa, Noah.
How algorithms create and prevent fake news
exploring the impacts of social media, deepfakes, GPT-3, and more /[electronic resource] :by Noah Giansiracusa. - Berkeley, CA :Apress :2021. - xii, 235 p. :ill., digital ;24 cm.
1. Perils of Pageview -- 2. Crafted by Computer -- 3. Deepfake Deception -- 4. Autoplay the Autocrats -- 5. Prevarication and the Polygraph -- 6. Gravitating to Google -- 7. Avarice of Advertising -- 8. Social Spread -- 9. Tools for Truth.
From deepfakes to GPT-3, deep learning is now powering a new assault on our ability to tell what's real and what's not, bringing a whole new algorithmic side to fake news. On the other hand, remarkable methods are being developed to help automate fact-checking and the detection of fake news and doctored media. Success in the modern business world requires you to understand these algorithmic currents, and to recognize the strengths, limits, and impacts of deep learning---especially when it comes to discerning the truth and differentiating fact from fiction. This book tells the stories of this algorithmic battle for the truth and how it impacts individuals and society at large. In doing so, it weaves together the human stories and what's at stake here, a simplified technical background on how these algorithms work, and an accessible survey of the research literature exploring these various topics. How Algorithms Create and Prevent Fake News is an accessible, broad account of the various ways that data-driven algorithms have been distorting reality and rendering the truth harder to grasp. From news aggregators to Google searches to YouTube recommendations to Facebook news feeds, the way we obtain information today is filtered through the lens of tech giant algorithms. The way data is collected, labelled, and stored has a big impact on the machine learning algorithms that are trained on it, and this is a main source of algorithmic bias - which gets amplified in harmful data feedback loops. Don't be afraid: with this book you'll see the remedies and technical solutions that are being applied to oppose these harmful trends. There is hope.
ISBN: 9781484271551$q(electronic bk.)
Standard No.: 10.1007/978-1-4842-7155-1doiSubjects--Topical Terms:
901893
Fake news
--Prevention.
LC Class. No.: QA76.9.A43 / G53 2021
Dewey Class. No.: 006.31
How algorithms create and prevent fake newsexploring the impacts of social media, deepfakes, GPT-3, and more /
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1. Perils of Pageview -- 2. Crafted by Computer -- 3. Deepfake Deception -- 4. Autoplay the Autocrats -- 5. Prevarication and the Polygraph -- 6. Gravitating to Google -- 7. Avarice of Advertising -- 8. Social Spread -- 9. Tools for Truth.
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From deepfakes to GPT-3, deep learning is now powering a new assault on our ability to tell what's real and what's not, bringing a whole new algorithmic side to fake news. On the other hand, remarkable methods are being developed to help automate fact-checking and the detection of fake news and doctored media. Success in the modern business world requires you to understand these algorithmic currents, and to recognize the strengths, limits, and impacts of deep learning---especially when it comes to discerning the truth and differentiating fact from fiction. This book tells the stories of this algorithmic battle for the truth and how it impacts individuals and society at large. In doing so, it weaves together the human stories and what's at stake here, a simplified technical background on how these algorithms work, and an accessible survey of the research literature exploring these various topics. How Algorithms Create and Prevent Fake News is an accessible, broad account of the various ways that data-driven algorithms have been distorting reality and rendering the truth harder to grasp. From news aggregators to Google searches to YouTube recommendations to Facebook news feeds, the way we obtain information today is filtered through the lens of tech giant algorithms. The way data is collected, labelled, and stored has a big impact on the machine learning algorithms that are trained on it, and this is a main source of algorithmic bias - which gets amplified in harmful data feedback loops. Don't be afraid: with this book you'll see the remedies and technical solutions that are being applied to oppose these harmful trends. There is hope.
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